虚拟仿真中的物理引擎线程设计与对象可扩展性

Sean C. Mondesire, Douglas B. Maxwell, Jonathan Stevens
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引用次数: 0

摘要

美国陆军研究实验室(ARL)正在研究增强下一代战术模拟教练机的技术和方法。一个主要的研究目标是增加同时可以在共享的虚拟环境中训练和协作的士兵数量。目前的虚拟项目记录不能支持陆军部在虚拟环境中对连梯队(200名士兵)进行训练的目标,并且仅限于排梯队(42名士兵)的并行受训者。ARL已经确定了限制可伸缩性的因素是模拟器的物理引擎和线程架构。在这项工作中,评估了两种线程设计在高物理负载下的表现,以确定哪种线程设计最适合未来的虚拟训练器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Physics Engine Threading Design and Object-Scalability in Virtual Simulation
The U.S. Army Research Laboratory (ARL) is investigating technologies and methods to enhance the next generation of tactical simulation-based trainers. A primary research objective is to increase the number of simultaneous Soldiers that can train and collaborate in a shared, virtual environment. Current virtual programs of record cannot support the Department of the Army's goal to train at the company echelon (200 Soldiers) in a virtual environment and are limited to the platoon echelon (42 Soldiers) of concurrent trainees. ARL has identified scalability limiting factors to be the simulator's physics engine and threading architecture. In this work, two threading designs are evaluated on how they perform with high amounts of physics load to determine which thread design is optimal for future virtual trainers.
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